Mohammed Y Said, Leah Ng'ang'a, Gert Nyberg, Shem Kifugo, Ewa Wredle, Anna Hallmén, Regina Waiganjo, Peter Mwangi, Jan de Leeuw

and Polly Ericksen

Measuring resilience—Understanding trends in land cover changes and their potential impacts on pastoral communities

IFPRI 2020 Policy Consultation and Conference, Side Event on Measuring and Evaluating Resilience in Drylands of East Africa,

Addis Ababa, 15-17 May 2014

Resilience framework

Source: Pasteur, K. 2012. From Vulnerability to Resilience A framework for analysis and action to build community resilience

“ … measure of the persistence of systems and of their ability to absorb change and disturbance and still maintain the same relationships between populations or state variables (Holling, 173)

Future uncertainty(Long term trends, climate change)

Adaptive capacity• Improving understanding of trends and

local impacts• Ensuring access to relevant and timely

information• Building confidence and flexibility to

learn and experiment

GovernanceEnabling environment

• Decentralized and participatory decision making

• Strengthening links between local district and national levels

• Promoting integrated approaches to livelihoods, disaster and climate change

• Addressing underlying systematic issues

Resilience• Ability to manage risk• Ability to adapt to

change • Ability to secure

sufficient food

Hazards and stressesDisaster preparedness

• Building capacity to analyse hazards and stresses

• Improving hazard prevention and protection

• Increase early warning and awareness• Establishing contingency and

emergency planning

LivelihoodsDiversity and security

• Strengthening community organization and voice

• Supporting access to, and sustainable management of productive assets

• Promoting access to technologies• Improving access to markets and

employment• Ensuring secure living conditions

Projected population and water use

Source: ACC 2014 Natural Capital Atlas

In 1960 Kenya population was less than 10 million by 2009 the had

increased to 40 million. This population will double to 80 million

by 2050

Growing human population and rise per capita use of resources is

depleting water supply in Kenya. High conservation and management will

be needed to deal with water shortages now and in the future.

Study sites – agro ecological potential

Source: KNBS, KSS, ILRI

1

32

6

54

7

8

1 = West Pokot; 2 = Elgeyo Marakwet; 3 = Baringo; 4 = Nyandarua; 5: Nyeri6 = Narok; 7 Machakos; 8 = Kwale

Human Population1962

2009

Causes of forest cover changes

Underlying cause

Source: Geist & Lambin 2002

Population dynamics

200 400 600 800 1000 1200 1400 16000.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

f(x) = 0.00180333497246733 x − 0.367073075263874R² = 0.808758516231781

1962Linear (1962)2009Linear (2009)

Rainfall (mm)

log

(Pop

ulati

on d

ensi

ty)

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

0

500000

1000000

1500000

2000000

2500000

BaringoElgeyo-MarakwetKwaleMachakosNarokNyandaruaNyeriWest Pokot

Popu

latio

n

Source: Said et al. (in prep)

Monitoring Vegetation condition using satellite

19841986

19881990

19921994

19961998

20002002

20042006

20080.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

BaringoElgeyo-MarakwetKwaleMachakosNarokNyandaruaNyeriWest Pokot

Years

Ndv

i

Source: Said et al. (in prep)

Trends in NDVI for the period 1982 -2008. A 3 year smoothing interval used to clearly show the trends

Framework - Relationship between population growth and vegetation

Influence of population growth on vegetation cover can be considered as two effects – consuming

constructive effect and constructive effect.

C = Consuming Destruction EffectD = Planting Construction Effect

Population density

Vege

tatio

n co

ver

C>DD>C

Population density

Vege

tatio

n co

ver

D>C C>D

Population density

Vege

tatio

n co

ver C>D D>C

Source: Li et al. 2013, Modified

Land cover changes Mau - Narok

200000 400000 600000 8000000.45

0.46

0.47

0.48

0.49

0.50

0.51

0.52

0.53

0.54

f(x) = − 6.51803772677525E-08 x + 0.53825198794027R² = 0.416814348632574

Population

NDV

I

Source: Said et al. (in prep), Leah (in prep), Hansen et al. 2013)

2001 2012 Change analysis 2001 -12

Impacts on livelihood and environment – southern Kenya rangelands

Jan-

77

Jan-

80

Jan-

83

Jan-

86

Jan-

89

Jan-

92

Jan-

95

Jan-

98

Jan-

01

Jan-

04

Jan-

07

Jan-

10

0200000400000600000800000

10000001200000140000016000001800000

Kajiado

ShoatsCattleWildliffe

Popu

latio

n si

ze

Jan-

77

Jan-

80

Jan-

83

Jan-

86

Jan-

89

Jan-

92

Jan-

95

Jan-

98

Jan-

01

Jan-

04

Jan-

07

Jan-

10

0

500000

1000000

1500000

2000000

2500000

Narok

ShoatsCattleWildlife

Popu

latio

n si

ze

Ogutu, Said, Kifugo in press

500000 550000 600000 650000 7000000.54

0.56

0.58

0.60

0.62

0.64

0.66

0.68

f(x) = 3.76996E-12 x² − 0.00000445952 x + 1.9120821R² = 0.30429688299913

Population

NDV

I

Land cover Mt Kenya - Nyeri

Source: Said et al. (in prep)

2001 2012 Change analysis 2001 -12

Framework - drylands

1983

2013

Source: Anna Hallmén, MSc Thesis 2014

Photos: Vi

Image showing changes in land cover – in 2013 the red tone colour indicates increase in tree cover

Efforts to increase tree cover started in the early 1980s by Vi Sweden in West Pokot. It started in schools and

churches and later extended to communal and private lands.

Land cover changes in West Pokot 1983 -2013

Impacts of enclosures on vegetationChepareria

100000 200000 300000 400000 5000000.45

0.46

0.47

0.48

0.49

0.50

0.51

0.52

0.53

0.54

0.55

f(x) = 1.38179363364949E-07 x + 0.467213836284635R² = 0.680361651211475

Population

NDV

I

enclosure open0%

20%

40%

60%

80%

100%

81%

51%

Tot

al p

lant

cov

er

closed open0

5

10

15

20

25

30

35

Fora

ge b

iom

ass

(g/m

2)

closed open0

2

4

6

8

10

12

14

Spec

ies

rich

ness

Source: Google maps

Source: Regina Waiganjo, MSc Thesis 2014; Said et al. (in prep)

Enclosures had more plant cover, biomass was four folds and species richness higher than the open grazing areas

Next steps

Socio - ecological changes

• What are the land cover dynamics and trajectories in the drylands of EA?

• What correlation can be established between climatic indicators and vegetation indexes?

• What type land health can we detect

• Potential for PES?

Livelihood challenges and opportunities

• Does the number of livestock, stocking rate and composition differ between pastoralists using enclosures compared with traditional nomadic pastoralists?

• Have a more sedentary lifestyle changed the roles in the family and the women’s economic empowerment?

• What are the trades-offs between sedentary and non-sedentary population?

Acknowledgement

Projects or programs: CRP 1.1, BMZ (Developing the livelihood income diversification potential of carbon sequestration in African drylands), Triple L (Students and Scientists)

Data: Department of Resource Surveys and Remote Sensing (DRSRS), Kenya National Bureau of Statistics (KNBS), Kenya Agriculture Research Institute - Kenya Soils Surveys (KSS), Vi West Pokot, NOAA, and Google.